The analysis of gene expression in hematopietic stem/progenitor cells (HSPCs; LSK cells, Lineage-, c-kit+, Sca-1+) from diabetic/nondiabetic mice.
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE117088 | GEO | 2021/05/14
REPOSITORIES: GEO
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Project description:Endothelial dysfunction promotes the pathogenesis of diabetic nephropathy (DN), which is considered to be an early event in disease progression. However, the molecular changes associated with glomerular endothelial cell (GEC) injury in early DN are not well defined. Most gene expression studies have relied on the indirect assessment of GEC injury from isolated glomeruli or renal cortices. Here, we present transcriptomic analysis of isolated GECs, using streptozotocin-induced diabetic wildtype (STZ-WT) and diabetic eNOS-null (STZ-eNOS−/−) mice as models of mild and advanced DN, respectively. GECs of both models in comparison to their respective nondiabetic controls showed significant alterations in the regulation of apoptosis, oxidative stress, and proliferation. The extent of these changes was greater in STZ-eNOS−/− than in STZ-WT GECs. Additionally, genes in STZ-eNOS−/− GECs indicated further dysregulation in angiogenesis and epigenetic regulation. Moreover, a biphasic change in the number of GECs, characterized by an initial increase and subsequent decrease over time, was observed only in STZ-eNOS−/− mice. This is consistent with an early compensatory angiogenic process followed by increased apoptosis, leading to an overall decrease in GEC survival in DN progression. From the genes altered in angiogenesis in STZ-eNOS−/− GECs, we identified potential candidate genes, Lrg1 and Gpr56, whose function may augment diabetes-induced angiogenesis. Thus, our results support a role for GEC in DN by providing direct evidence for alterations of GEC gene expression and molecular pathways. Candidate genes of specific pathways, such as Lrg1 and Gpr56, can be further explored for potential therapeutic targeting to mitigate the initiation and progression of DN.
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Project description:In the present study, we aimed to determine the genes involved in inflammatory process of diabetic nephropathy. ICAM-1+/+ and ICAM-1-/- mice aged 8 weeks were divided into four groups: 1) nondiabetic ICAM-1+/+ mice (ND-WT), 2) nondiabetic ICAM-1-/- mice (ND-KO), 3) streptozotocin (STZ)-induced diabetic ICAM-1+/+ mice (DM-WT), and 4) STZ-induced diabetic ICAM-1-/- mice (DM-KO). Three months after the induction of diabetes, total RNA was extracted from each specimen of renal cortex. We examined gene expression profiles of four groups. We identified 193 genes; the ratio of expression level of DM-WT was >2 or <0.5 of that of DM-KO. Of 193 genes, hierarchical clustering identified 33 genes that were significantly upregulated only in DM-WT but not remarkable in ND-WT and ND-KO. Functional annotation of these 33 genes revealed that the significant functions of them were related to the immune or inflammatory process: immune response, response to stimulus, defense response, immune effector process and antigen processing and presentation. These genes contained several inflammatory related genes, such as chemokine (C-X-C motif) ligand 10, chemokine (c-c motif) ligand 12, and chemokine (c-c motif) ligand 8. In this cluster, we focused on cholecystokinin (CCK) because CCK is one of the most up-regulated genes. Real-time RT-PCR revealed that CCK mRNA expression was significantly up-regulated in DM-WT compared with DM-KO. These results suggest that CCK may play a critical role in the progression of diabetic nephropathy by controlling inflammation in diabetic kidney.
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Functional annotation of these 33 genes revealed that the significant functions of them were related to the immune or inflammatory process: immune response, response to stimulus, defense response, immune effector process and antigen processing and presentation. These genes contained several inflammatory related genes, such as chemokine (C-X-C motif) ligand 10, chemokine (c-c motif) ligand 12, and chemokine (c-c motif) ligand 8. In this cluster, we focused on cholecystokinin (CCK) because CCK is one of the most up-regulated genes. Real-time RT-PCR revealed that CCK mRNA expression was significantly up-regulated in DM-WT compared with DM-KO. These results suggest that CCK may play a critical role in the progression of diabetic nephropathy by controlling inflammation in diabetic kidney. Male ICAM-1-/- mice (C57BL/6J background) were purchased from The Jackson Laboratory (Bar Harbor, ME). Male C57BL/6J mice (ICAM-1+/+) mice were used as controls. ICAM-1+/+ and ICAM-1-/- mice aged 8 weeks were divided into four groups (n = 5 each): 1) nondiabetic ICAM-1+/+ mice (ND-WT), 2) nondiabetic ICAM-1-/- mice (ND-KO), 3) streptozotocin (STZ)-induced diabetic ICAM-1+/+ mice (DM-WT), and 4) STZ-induced diabetic ICAM-1-/- mice (DM-KO). Mice in the diabetic groups received an intraperitoneal injection of STZ (Sigma Chemical, St.Louis, MO) at 200 mg/kg in citrate buffer (pH 4.5). Blood glucose levels were determined 7 days after STZ injection and only mice with blood glucose concentrations >16 mmol/L were used in the study. Nondiabetic ICAM-1+/+ and ICAM-1-/- mice received citrate buffer injections only. All mice had free access to standard diet and tap water. All animal procedures were performed according to the Guidelines for Animal Experiments at Okayama University Medical School, Japanese Government Animal Protection and Management Law (no. 105), and Japanese Government Notification on Feeding and Safekeeping of Animals (no. 6). Three months after the induction of diabetes, all mice were killed, and the kidneys were harvested. Total RNA was extracted from each specimen of renal cortex using standard protocol from RNeasy midi kit (Qiagen, Valencia, CA) at 3 months. The concentration and the quality of the total RNA sample were assessed by Agilent Bioanalyzer. Biotin-labeled target cRNA was prepared using First and Second strand cDNA Synthesis Kit (Amersham Biosciences, No. 320000) and In Vitro Transcription Kit (Amersham Biosciences, No.320001). Incubate total RNA (5 μg), diluted bacterial mRNA spike controls and T7 oligo (dT) primer for 10 min at 70 C. Add first-strand reaction components and incubate 1 hour at 42C. Add the first-strand cDNA product to the second-strand reaction components and incubate for 2 hours at 16 C. Double-strand cDNA was purified using QIAquick purification kit (Qiagen), eluted twice, each time with 30μl of nuclease-free water then dried in a SpeedVac concentrator. Prepare IVT mix of biotinylated UTP, ribonucleotides, and the 10x T7 enzyme mix and add to the resuspended cDNA. Incubate at 37C for 14 hours. Purify cRNA using RNeasy Mini Kit (Qiagen) and elute the cRNA twice, each time with 50 μl nuclease-free water. Measure the absorbance at 260 nm and 280 nm to determine the ratio (A260:A280=2). In 25 μl total volume, add 10 μg of cRNA to 5 μl of 5x fragmentation buffer and incubate at 94 C for 20 min. Bring 10 μg of fragmented cRNA, 78 μl of hybridization buffer component A, and 130 μl of hybridization buffer component B to a final volume of 260 μl with water. Incubate at 90C for 5 min and immediately chill on ice for 5 min. Slowly inject 250 μl of hybridization reaction mixture into array input port and seal ports with sealing strips. Set the shaker speed to 300 rpm and incubate slides for 18 hours at 37C in an Innove 4080 shaker. Remove the Flex Chamber using the hybridization removal tool. Then, place the bioarrays into the bioarray rack while it sits inside the medium reagent reservoir containing 0.75xTNT. Transfer the bioarray rack to the large reagent reservoir containing preheated 0.75xTNT, and incubate at 46 C for exactly 1 hour. Fill each slot of the small reagent reservoir with 3.4 ml of Cy5-Streptavidin working solution. Transfer the bioarray rack from the large reagent reservoir in to the small reagent reservoir and incubate bioarrays at RT for 30 min. Wash the bioarrays four times with 1xTNT at RT for 5 min. Rinse the bioarrays in 0.1xSSC/0.05%Tween by moving rack up and down 5 times in 5 seconds. Immediately follow the rinse with centrifugation to dry bioarrays, and store dried bioarrays in the dark. We scanned bioarrays with Axon GenePix 4000B and analyzed with CodeLink Expression Analysis software version 2.3.2. The 10,000 spot intensities on the scanned microarray image were normalized to a median value of 1 and data were exported for analysis with CodeLink Expression Analysis software version 2.3.2
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